Search results for "feature"
showing 10 items of 4091 documents
GEOLOGIA DE LAS MARGENES DE LA PLACA DEL CARIBE: GENERALIDADES EN GUATEMALA, COSTA RICA, LA ESPAÑOLA Y RESULTADOS PRELIMINARES DEL ANALISIS DE UNA TR…
2011
The Caribbean Plate margins are constituted by deformed belts built up since the Cretaceous in acompressional and strike-slip stress field, which allowed overthrusting of the Caribbean crust onto the Pacific,North and South American Plates.The Caribbean borders include Jurassic-Cretaceous ophiolitic units (Great Antilles, Venezuela, Costa Rica,Guatemala, etc.), composed by mantle peridotites, gabbros, volcanic and sedimentary covers, which have beendeformed in at least two ductile penetrative phases and were often metamorphosed in the prehnite-pumpelleyite,green and blue schist, amphibolite, and in places eclogite facies. These units may present part of a subductioncomplex or are an accreti…
Structural analysis of a complex nappe sequence and late-orogenic basins from the Aegean Island of Samos, Greece
1999
The island of Samos in the Aegean Sea exposes high-pressure metamorphic rocks of the Cycladic blueschist unit which are sandwiched between the mildly blueschist-facies Kerketas nappe below and the overlying non-metamorphic Kallithea nappe. Structural and metamorphic analysis shows that deformation can generally be divided into four main stages: (1) Eocene and earliest Oligocene 0ESE‐WNW-oriented nappe stacking (D1 and D2) associated with blueschist- and transitional blueschist‐ greenschist-facies metamorphism (M1 and M2). D2 caused emplacement of the blueschist unit onto the Kerketas nappe indicating that thrusting occurred during decompression. (2) A subsequent history of Oligocene and Mio…
3-D attenuation image of fluid storage and tectonic interactions across the Pollino fault network
2021
SUMMARYThe Pollino range is a region of slow deformation where earthquakes generally nucleate on low-angle normal faults. Recent studies have mapped fault structures and identified fluid-related dynamics responsible for historical and recent seismicity in the area. Here, we apply the coda-normalization method at multiple frequencies and scales to image the 3-D P-wave attenuation (QP) properties of its slowly deforming fault network. The wide-scale average attenuation properties of the Pollino range are typical for a stable continental block, with a dependence of QP on frequency of $Q_\mathrm{ P}^{-1}=(0.0011\pm 0.0008) f^{(0.36\pm 0.32)}$. Using only waveforms comprised in the area of seism…
Microremains from El Mirón Cave human dental calculus suggest a mixed plant/animal subsistence economy during the Magdalenian in Northern Iberia
2015
Abstract Despite more than a century of detailed investigation of the Magdalenian period in Northern Iberia, our understanding of the diets during this period is limited. Methodologies for the reconstruction of Late Glacial subsistence strategies have overwhelmingly targeted animal exploitation, thus revealing only a portion of the dietary spectrum. Retrieving food debris from calculus offers a means to provide missing information on other components of diet. We undertook analysis of human dental calculus samples from Magdalenian individuals (including the “Red Lady”) at El Miron Cave (Cantabria, Spain), as well as several control samples, to better understand the less visible dietary compo…
Processing of rock core microtomography images: Using seven different machine learning algorithms
2016
The abilities of machine learning algorithms to process X-ray microtomographic rock images were determined. The study focused on the use of unsupervised, supervised, and ensemble clustering techniques, to segment X-ray computer microtomography rock images and to estimate the pore spaces and pore size diameters in the rocks. The unsupervised k-means technique gave the fastest processing time and the supervised least squares support vector machine technique gave the slowest processing time. Multiphase assemblages of solid phases (minerals and finely grained minerals) and the pore phase were found on visual inspection of the images. In general, the accuracy in terms of porosity values and pore…
Learning to Navigate in the Gaussian Mixture Surface
2021
In the last years, deep learning models have achieved remarkable generalization capability on computer vision tasks, obtaining excellent results in fine-grained classification problems. Sophisticated approaches based-on discriminative feature learning via patches have been proposed in the literature, boosting the model performances and achieving the state-of-the-art over well-known datasets. Cross-Entropy (CE) loss function is commonly used to enhance the discriminative power of the deep learned features, encouraging the separability between the classes. However, observing the activation map generated by these models in the hidden layer, we realize that many image regions with low discrimin…
Real-time flaw detection on a complex object: comparison of results using classification with a support vector machine, boosting, and hyperrectangle-…
2006
We present a classification work performed on industrial parts using artificial vision, a support vector machine (SVM), boost- ing, and a combination of classifiers. The object to be controlled is a coated heater used in television sets. Our project consists of detect- ing anomalies under manufacturer production, as well as in classi- fying the anomalies among 20 listed categories. Manufacturer speci- fications require a minimum of ten inspections per second without a decrease in the quality of the produced parts. This problem is ad- dressed by using a classification system relying on real-time ma- chine vision. To fulfill both real-time and quality constraints, three classification algorit…
Improving clustering of Web bot and human sessions by applying Principal Component Analysis
2019
View references (18) The paper addresses the problem of modeling Web sessions of bots and legitimate users (humans) as feature vectors for their use at the input of classification models. So far many different features to discriminate bots’ and humans’ navigational patterns have been considered in session models but very few studies were devoted to feature selection and dimensionality reduction in the context of bot detection. We propose applying Principal Component Analysis (PCA) to develop improved session models based on predictor variables being efficient discriminants of Web bots. The proposed models are used in session clustering, whose performance is evaluated in terms of the purity …
Class discovery from semi-structured EEG data for affective computing and personalisation
2017
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. Many approaches to recognising emotions from metrical data such as EEG signals rely on identifying a very small number of classes and to train a classifier. The interpretation of these classes varies from a single emotion such as stress [24] to features of emotional model such as valence-arousal [4]. There are two major issues here. First classification approach limits the analysis of the data within the selected classes and is also highly dependent on training data/cycles, all of which limits generalisation. Second issue is that it does not exp…
Dynamic Community Detection for Brain Functional Networks during Music Listening with Block Component Analysis
2023
Publisher Copyright: Author The human brain can be described as a complex network of functional connections between distinct regions, referred to as the brain functional network. Recent studies show that the functional network is a dynamic process and its community structure evolves with time during continuous task performance. Consequently, it is important for the understanding of the human brain to develop dynamic community detection techniques for such time-varying functional networks. Here, we propose a temporal clustering framework based on a set of network generative models and surprisingly it can be linked to Block Component Analysis to detect and track the latent community structure…